Abstract:MolMod is both a reagents database and a tool for drug discovery. It uses ChemAxon tools and APIs to provide ways to store, search and filter reagents and their containers thanks to several kinds of criterias (structure, sub-structure, vendor, formula, molecular weight, activity...) It also allows to perform virtual reactions between user-given molecules or between every reagents stored in the database, in order to create new compounds. Finally, it includes descriptors searches (ie Fuzzy Tricentric Pharmacophores) and similarity searches, on user-given molecules or on databases reagents.

Abstract:Modern drug discovery relies heavily on large-scale high-throughput screening (HTS) to identify potential starting points for medicinal chemistry optimization. The typical “top X” activity cutoff method used to generate hits from large amount of raw HTS data is intrinsically error-prone due to the noisy nature of single-dose HTS, which oftentimes leads to a large number of false positives. Here we propose a novel knowledge-based, SAR-driven statistical approach for primary HTS hit generation using ChemAxon technology for clustering and chemical fingerprints. The method is also implemented with SciTegic Pipeline Pilot. In a proof-of-concept study for an in-house HTS campaign, the new approach proved to be more effective in identifying confirmed active compounds in diverse chemical scaffolds containing valuable SAR information, as demonstrated by a significantly improved confirmation rate compared to the traditional “top X” cutoff method.

Abstract:A step by step approach of how Inhibox have assembled and implemented ChemAxon API’s and cartridge functionality in Oracle and Java, to build a molecule data warehouse to support virtual screening activity. An emphasis on providing data sets that cover the chemical space succinctly for a given target space, how tangible commercial space is used and transformed into virtual Chemical space using reactor, and how resolved, conformer and 3D data fit into the subsequent screening protocols employed at Inhibox are the main themes. All ChemAxon functionality / implementation details at each stage will be well defined.

Abstract:The BioPrint database consists of an homogeneous set of in-house generated experimental data consisting of more than 2400 compounds profiled under standardized conditions with respect to more than 170 well-characterized in-vitro assays. Molecular modeling tools have been developed and combined with this high quality dataset to allow QSAR models generation, pharmacological profile prediction, and best compharm overlay superposition search.

Abstract: The three tools introduced in this poster solve some straightforward integration problems. We believe however that it is through solving such integration problems that increases in productivity for both researchers and IT staff can be gained.
Corporate databases are sometimes treated as little more than an archive, in spite of the fact that they store a lot of valuable data. The difficulty researchers’ face in accessing corporate data stores sometimes acts as a barrier to them using that data at all. JEX Connector and JS Connector enable easy access to corporate databases from a context familiar to all researchers, Excel or Spotfire. When integrated into large custom systems these tools help IT people to reduce coding time and training effort required to get end users the data they need.

Abstract:The Accamba project (http://accamba.imag.fr/) is a collaborative multidisciplinary project supported by the French ministry of research, involving biologists, chemists and computer scientists. Its main objective is to develop tools in order to analyse chemical libraries and to model screening results using Machine Learning approaches. In this poster, we present a general overview of the Accamba approach and we focus on the benefits brought by using ChemAxon software tools in various stages of this project. We use Marvin beans in our screening results analysis software, Standardizer to detect automatically chemical errors and redundancies when we receive molecules databases, to clean them and normalize molecules, Calculator Plugins to compute relevant molecular descriptors, API from Screen and Klustor to make comparative studies with the new distance algorithm that we are developing in this project.In the future, we would like to allow the biologist user to better exploit our screening results database by adding structural search using ChemAxon Tools (JChem Base, Marvin beans…). We also think to use Reactor to investigate about the advantages of a virtual synthesis stage to help chemists in the Accamba project.

Abstract:Dictionary of Natural Products (The Chapman & Hall) is a collection of chemical substances of natural sources updated twice a year. The data are catalogized, and this is the only way to retrieve information from the database. It was decided to make the database searchable and available to all researchers at the company. The data were placed in an ORACLE database including the chemical structures of the substances. The structures are converted and processed with JChem. The query interface is a web application employing the Java Server Pages (JSP) technology. The most important fields (id, full chemistry name, CAS number, molecular weight, importance, and pharmaceutical importance) and the chemical structure are selected to be searchable. The chemical structure entry is done with MarvinSketch applet in the query. The alphanumeric search is conducted in ORACLE using JDBC and the chemical structure search is using JChem. The chemical structures in the results of the query are presented with MarvinView applet. Besides the searchable fields and the chemical structure, the bibliographic references are displayed.

Abstract:Nowadays, new communication and information technologies give access to an important quantity of specific data. However, in chemoinformatics, such data are often too generic, focused on a single application field and not suited to a precise problem. Consequently, we generated and conceived several databases allowing the crossing of miscellaneous information. The first one called “Bioinfo”, is a library of 1.8 million commercially available drug-like compounds that can be use in the framework of the in silico ligand-based drug design. The second one named "screening-Protein Data Bank" (sc-PDB) is a collection of 6415 druggable binding sites from proteins whose x-ray structure has been deposited in the Protein Data Bank (PDB). The last one, “human G-Protein Coupled Receptors & ligands” (hGPCR-lig), is a collection of human GPCR (369) and their ligands (+17000), also classified according to the diversity of receptor binding sites and their ligands, respectively.

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